Optimal Stochastic Control Problem for General Linear Dynamical Systems in Neuroscience. (17th December 2017)

• Record Type: Journal Article
• Authors: Chen, Yan; Deng, Yingchun; Yue, Shengjie; Deng, Chao
• Other Names: Leoncini Xavier Academic Editor.
• Is Part Of: Advances in mathematical physics. Volume 2017(2017)
• Publication Date: 2017-12-17
• Subjects: Mathematical physics -- Periodicals; Mathematical physics; Periodicals; 530.15
• DOI: 10.1155/2017/8730859
• Languages: English
• ISSNs: 1687-9120

Abstract

Abstract : This paper considers a d -dimensional stochastic optimization problem in neuroscience. Suppose the arm's movement trajectory is modeled by high-order linear stochastic differential dynamic system in d -dimensional space, the optimal trajectory, velocity, and variance are explicitly obtained by using stochastic control method, which allows us to analytically establish exact relationships between various quantities. Moreover, the optimal trajectory is almost a straight line for a reaching movement; the optimal velocity bell-shaped and the optimal variance are consistent with the experimental Fitts law; that is, the longer the time of a reaching movement, the higher the accuracy of arriving at the target position, and the results can be directly applied to designing a reaching movement performed by a robotic arm in a more general environment.